Diagnostic Imaging's Weekly Scan: July 19 — July 25

Welcome to Diagnostic Imaging’s Weekly Scan, which offers an opportunity to catch up on the most well-viewed radiology content of the past week.

In a new comparative study involving 51 women who had systemic treatment for metastatic breast cancer, researchers found that all FDG-PET scans identified measurable target lesions according to PERCIST criteria in comparison to 35 percent of CT scans as per RECIST 1.1 criteria.

In a recent interview with Diagnostic Imaging, Vivek Singh, MD, discussed the practical realities of integrating AI into neuroradiology workflows, addressing challenges and concerns with implementation and potential automation bias, and emphasizing the importance of appropriate governance with AI tools and measurable outcomes in stroke imaging.

In another interview with Diagnostic Imaging, Kenneth Chan, MBBS, discussed new research, presented at the recent Society of Cardiovascular Computed Tomography (SCCT) conference, that showed the impact of coronary inflammation in identifying elevated cardiovascular risk in patients with zero or low coronary artery calcium (CAC) scores.

General radiologist assessment of mammograms with adjunctive AI led to a significant increase in cancer detection rate akin to that of breast imaging specialists, according to new research published in the Radiology journal earlier this week.

A model combining MRI and ultrasound findings yielded a 93 percent AUC for predicting microvascular invasion in hepatocellular carcinoma, according to a new meta-analysis published in the European Journal of Radiology.